Systems dynamics and casual configurations: Using dynamic pattern synthesis for macroeconomic comparative research

David Alemna, Philip Haynes

Research output: Contribution to journalArticlepeer-review

Abstract

Dynamic Pattern Synthesis (DPS) provides a new longitudinal method for evaluating the impacts of macroeconomic and public policy interventions. Situated within complexity theory and critical realism, it has evolved from the established methods of Cluster Analysis and Configurational Modelling approaches. Dynamic Pattern Synthesis identifies case convergence and divergence (using quantitative techniques), while remaining close to the qualitative uniqueness of each case. In this paper, the DPS approach is used to consider macroeconomic convergence across Sub-Saharan Africa during the Millennium Development Goals, and the possible impacts of IMF interventions in stimulating long-term macroeconomic outcomes. The findings reveal a high degree of economic instability experienced across the region and varying responses to an external shock. The importance of ‘outliers’ and inconsistency in country convergence are also observed. The DPS method highlights the importance of individual country experiences in relation to external shocks. When factoring in IMF interventions, the findings highlight multiple paths to a given policy outcome, rather than a single optimal economic strategy. This opens up the debate on policy issues associated with economic complexity, including how best to create an overall environment of stability that might promote convergence and reduce the instability that undermines planning and investment.
Original languageEnglish
Number of pages13
JournalMethodological Innovations
DOIs
Publication statusPublished - 10 Jun 2024

Keywords

  • Cluster analysis
  • Configurational modelling
  • Convergence
  • Sub-Saharan Africa

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